Aircraft efficiency is a critical factor for airline profitability. A one percent performance improvement (1% fuel use reduction) for a fleet of transport aircraft can result in great savings, as much as approximately $100 million per year for the United States fleet of wide-body aircraft at current fuel costs (55 cents per gallon) and an additional $20 million per year for each ten cents per gallon increase in fuel price.
Development of a significant amount of transport efficiency technology that started in the 1970's and 1980's has continued into the 1990's. An aircraft energy efficiency (ACEE) program explored maneuver load control, elastic mode suppression, gust load alleviations (J. F. Johnson, "Accelerated Development and Flight Evaluation of Active Controls Concepts for Subsonic Transport Aircraft--Volume I--Load Alleviation/Extended Span Development and Flight Tests," NASA CR-172277, 1984 ), relaxed static stability (W. A. Guinn, J. J. Rising and W. J. Davis, "Development of an Advanced Pitch Active Control System for a Wide Body Jet Aircraft," NASA CR-172277, 1984) and reduced-area horizontal tail design (J. J. Rising, "Development of a Reduced Area Horizontal Tail for a Wide Body Jet Aircraft," NASA CR-172278, 1984). An advanced F-111 fighter technology integration Mission Adaptive Wing (MAW) program developed and demonstrated variable-camber control for optimization of cruise and maneuver flight conditions ("Advanced Fighter Technology Integration F-111 Mission Adaptive Wing (ITAR), NASA CP-3055, 1990; E. L. Friend, "Flight Buffet Characteristics of a Smooth Variable-Camber Mission Adaptive Wing for Selected Wing Flap Deflections (ITAR), NASA TM-4455, 1993).
A member of the Airbus Industries team performed preliminary design work and wind-tunnel testing for implementing variable camber as a redundant effector in the A330/A340 aircraft. Benefits of variable camber include improved aerodynamic efficiency through improved lift-to-drag ratio (L/D), increased Mach number (M) capability, improved buffet boundary, increased operational flexibility, reduced structural weight and reduced fuel burn. Variable camber has also increased aircraft development potential. However, the proposed use of a variable camber design as a redundant effector did not include development of a real-time adaptive performance optimization methodology.
J. J. Spillman has provided an excellent dissertation relative to the fundamentals of variable camber as applied to transports ("The Use of Variable Camber to Reduce Drag, Weight and Costs of Transport Aircraft," Aeronautical Journal, Vol. 96, January 1992, pp. 1-9).
American manufacturers have also been actively involved in efficiency enhancement and have explored and implemented fixed-point rerigging of redundant control effectors to minimize airframe drag ("Long Live the Leviathan," Flight International, Sep. 15-21, 1993, pp. 30-31 and Guy Norris, "New MD-11 Update Revealed," Flight International, Dec. 21, 1994-Jan. 3, 1995, page 9).
The literature is replete with reports documenting trajectory optimization algorithms and their benefits relative to the economics of commercial transports. In fact, all large transports currently being produced have computer-based Flight Management Systems (FMS) that optimize the aircraft trajectory to minimize cost as a function of flight time and fuel price. However, the common basis for these algorithms are models of performance-related aspects of the particular aircraft model under specific flight conditions. As a result, the optimal trajectory is only as good as the onboard FMS models. In addition to the baseline onboard model having less than perfect accuracy, airframe and propulsion system degradation are factors which affect model accuracy.
NASA's Dryden Flight Research Center (DFRC), at Edwards, Air Force Base, California is active in transitioning performance improvement technology to transport aircraft (Glenn B. Gilyard and Martin D. Espana, "On the Use of Controls for Subsonic Transport Performance Improvement: Overview and Future Directions," NASA TM-4605, 1994). Realizable performance benefits are smaller for transport aircraft than for high performance fighter aircraft. The designs of most transports have already been highly refined for good performance under a steady-state cruise flight condition. An algorithm developed on a Performance-Seeking Control (PSC) program was useful as an early demonstration of the benefits to be accrued on performance aircraft with detailed models available, though not suitable for implementing further performance optimization on transports primarily because of the fact that the algorithm was heavily based on a priori model data and absolute measurement accuracy (Glenn B. Gilyard and John S. Orme, "Performance Seeking Control: Program Overview and Future Directions," NASA TM-4531, 1993). Consequently, DFRC is exploring the application of measurement-based APO for performance improvement on transports using redundant control effectors.
Adaptive Control Background
Application of adaptive control to aircraft has been ongoing for more than 30 years with varying degrees of success. These applications have often centered on handling quality-related control system improvements, which often involve optimizing a very subjective, often ill-defined criteria typically involving handling qualities, for example, pilot ratings. Because of the subjective nature of handling qualities, adaptive control techniques are not necessarily well-suited approaches to the problem. Also note that in many flight control applications, use of adaptive techniques has led to safety concerns about gain and phase margin reductions. Such reductions have contributed to stability and control problems.
As such, adaptive control, as applied to flight control, has not found wide acceptance within the aerospace community. Lack of interest in adaptive control is partially caused by the satisfactory results that have been obtained using conventional design techniques and by lack of an overriding reason to obtain similar results by using more complex techniques.
Application of adaptive control is particularly advantageous when the optimization objective is well defined and there are significant unknowns about the aircraft and its operation. Application of adaptive optimal control to quasi-steady performance optimization has clear benefits that are not achievable in control design processes that are tailored to handling qualities issues. Quasi-steady performance optimization has well-defined objectives (i.e., minimize drag). For this reason, adaptive optimal control is well-suited to performance optimization. In addition, application of adaptive optimal control, using a measured performance metric, is insensitive to modeling inaccuracies and measurement biases. Because low frequency constrained maneuvers are proposed, stability- and control-related safety issues and affects on ride qualities are greatly minimized.
Regarding work of the Airbus Industrie team and Americans involved in exploring variable-camber performance optimization, neither side has devoted serious attention to a real-time Adaptive Performance Optimization (APO) algorithm. The Americans used either predetermined deflection schedules or a real-time, trial-and-error approach for camber control (Advanced Fighter Technology Integration F-111 Mission Adaptive Wing (ITAR), NASA CP-3055, 1990, and P. W. Phillips, and S. b. Smith, AFTI/F-111 Mission Adaptive Wing (MAW) Automatic Flight Control System Modes Lift and Drag Characteristics, AFFTC-TR-89-03, May 1989). In the case of the Airbus Industrie team, only model-based or experimentally determined scheduling was briefly mentioned as a means of camber control (J. Szodruch and R. Hilbig, "Variable Wing Camber for Transport Aircraft," Progress in Aerospace Sciences, Vol. 25. No. 3, 1988, pp. 297-328).
Application of adaptive optimal techniques to performance optimization does not require accurate models or absolute measurements. The adaptive optimal approach is based on real-time estimation of gradients of performance measures to control variables. These gradients are based on flight measurements and not based on predictions, except as noted herein below. In addition, because gradients are used, the approach is insensitive to measurement biases.
An adaptive optimal approach is ideally suited for use on operational "fleet" aircraft where there is uncertainty in the aircraft model and absolute measurement accuracy. Likewise, adaptive performance techniques have a valuable role for commercial aircraft where small benefits over a 20-30 yr service life can produce significant cost savings.
Many issues enter into the performance optimization problem for subsonic transport aircraft. Foremost, there must be the potential for optimization, which implies redundant control effector capability (i.e., more than one means of trimming out the forces and moments to maintain a steady-state flight condition). Most aircraft have significant capability in this area although taking advantage of this capability is a different issue. Performing optimization from a condition that is already fine-tuned (based on wind tunnel and flight testing) places increased demands on high-quality instrumentation to sense small differences in an unsteady environment.
APO compensates for all unique characteristics of the aircraft flight control system by continuously feeding back measurements of parameters that reflect the optimization objective, such as fuel flow (minimize) or velocity (maximize). A specific example is the use of symmetric aileron deflection in an algorithm applied to optimally recamber the wing for all aircraft configurations and flight conditions to optimize (maximize) lift-to-(drag ratio which can in turn be utilized to produce: minimum fuel flow, maximum Mach number, maximum altitude or maximum loiter time.
A feasibility study by Glenn Gilyard explored a prototype adaptive control law on a high-fidelity, nonlinear simulation of a first-generation wide-body jet aircraft that optimized wing-aileron camber for minimum aircraft drag at a given flight condition ("Development of a Real-Time Transport Performance Optimization Methodology," NASA TM-4730, 1996). This technology applies tc selected current generation aircraft and could be a requirement for future designs, such as proposed new large aircraft.
Challenge for Present and Future Aircraft
The APO of the present invention could play an important role in improving economic factors for the operation of aircraft. The challenge to in-flight performance optimization for subsonic and supersonic transport aircraft and fighters is the identification and minimization of very low levels of incremental drag. This is the key technological challenge because in order to provide an effective performance optimization algorithm, identification of incremental drag levels of one percent or less are required.